Summary
β¨ AIβGenerated
A project-based engineering role for a hands-on builder who can design AI-powered automation and integrations for complex operational workflows. You will help automate the process of interpreting customer requests, gathering and comparing external data, applying business rules, generating quotations, and maintaining connected information systems.
Highlights
A project-based opportunity with openness to experienced professionals, freelancers, recent graduates, and strong university students. The role provides substantial ownership in designing an AI-enabled automation workflow and modernizing repetitive business processes.
Description
About LAC
Latin American Cargo (LAC) is a Montreal-based international freight-forwarding company serving customers throughout the Americas across ocean, air, and ground transportation.
We are beginning a company-wide initiative to use AI, workflow automation, and system integrations to reduce repetitive manual work and create better-connected internal processes.
We are looking for a technically strong builder to help design and implement the first major part of this initiative: an AI-enabled freight pricing and quotation workflow.
This is a project-based engagement.
We are open to experienced professionals, freelancers, recent graduates, and highly capable university students who can demonstrate relevant hands-on work.
The Project
Our pricing process involves receiving customer freight inquiries, interpreting shipment requirements, obtaining rates from multiple external sources, comparing options, applying internal pricing rules, preparing quotations, and maintaining information in our transportation-management system.
The initial goal is to automate a significant portion of this workflow while maintaining appropriate human review and control.
At a high level, the system will need to support:
Inbound inquiry β structured shipment data β rate retrieval β pricing logic β quote preparation β system integration β review/approval
Rate information may need to be obtained through a combination of APIs and authenticated online provider portals, so the solution may involve both traditional system integrations and secure browser automation.
Broader Architecture
This project is intended to become the first component of a larger internal AI and automation platform, not a standalone bot.
Future workflows across different areas of the company should be able to connect to the same underlying architecture, data, integrations, and knowledge rather than being developed as isolated automations.
We are therefore looking for someone who can think beyond the immediate workflow and design the foundation in a way that is maintainable and expandable.
What You'll Work On
You will work with LAC leadership and the people currently performing the pricing process to:
Understand the existing workflow and translate business requirements into a practical technical architecture.Build automated workflows using n8n or comparable workflow-automation technology.Build AI-assisted workflows that interpret inbound emails and convert unstructured shipment requests into structured data.Validate required information and appropriately handle incomplete or unclear requests.Automate live freight-rate retrieval from multiple external systems using APIs where available and secure browser automation where necessary.Normalize and compare information returned by different rate sources.Implement reliable pricing calculations based on business rules defined by LAC.Generate structured quote information and integrate the workflow with CargoWise, reducing repetitive manual entry.Integrate with Microsoft 365 and other relevant business systems where required.Design appropriate human review and approval points for exceptions and higher-risk decisions.Build proper error handling, logging, retries, alerts, and monitoring.Design the system with security, maintainability, scalability, and AI/API usage costs in mind.Document the architecture, integrations, workflows, and key technical decisions so the system can be maintained and expanded over time.
What We're Looking For
We are looking for someone who has experience building systems, not only experimenting with AI prompts.
Relevant experience may include:
n8n, Make, Zapier, or comparable workflow-automation platforms.REST APIs, webhooks, JSON, authentication, and third-party integrations.AI/LLM APIs such as OpenAI, Anthropic, or similar.SQL and relational databases.PostgreSQL, Supabase, or comparable data platforms.Structured extraction from emails, documents, and other unstructured information.Browser automation/RPA using Playwright, Puppeteer, Selenium, or similar tools.Designing workflows that combine AI with deterministic business rules.Error handling, logging, monitoring, and production troubleshooting.Designing systems that can support additional workflows and integrations over time.Clear technical documentation and communication.
Strongly Preferred
Experience with CargoWise, transportation-management systems, logistics technology, Microsoft 365 integrations, or other complex business-system integrations would be particularly valuable.
Freight-forwarding experience is helpful but is not required if you are comfortable learning the business processes behind the technology.
Who This Could Be a Good Fit For
We care more about what you can build than how many years are on your resume.
We welcome applications from experienced automation/integration engineers, freelancers, software developers, recent graduates, and advanced university students with substantial hands-on project experience.
Early-career applicants should be prepared to show relevant GitHub projects, demos, portfolio work, or other examples of systems they have personally built.
Engagement
Location: Remote β Canada
Type: Project-based / contract
Schedule: Flexible, with availability for occasional meetings during North American business hours
Duration: Based on initial discovery and agreed implementation scope
Compensation: Based on experience and engagement structure
Potential continuation: The successful implementation of this project may lead to additional automation and integration work as LAC expands the platform.